Stone detection in MRCP images using controlled region growing

Stones in the biliary tract are routinely identified using MRCP (magnetic resonance cholangiopancreatography). The noisy nature of the images, as well as varying intensity, size and location of the stones, defeat most automatic detection algorithms, making computer-aided diagnosis difficult. This pa...

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Main Authors: LOGESWARAN, R, ESWARAN, C
Format: Article
Published: PERGAMON-ELSEVIER SCIENCE LTD 2007
Subjects:
Online Access:http://shdl.mmu.edu.my/3022/
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author LOGESWARAN, R
ESWARAN, C
author_facet LOGESWARAN, R
ESWARAN, C
author_sort LOGESWARAN, R
building MMU Institutional Repository
collection Online Access
description Stones in the biliary tract are routinely identified using MRCP (magnetic resonance cholangiopancreatography). The noisy nature of the images, as well as varying intensity, size and location of the stones, defeat most automatic detection algorithms, making computer-aided diagnosis difficult. This paper proposes a multi-stage segment-based scheme for semi-automated detection of choledocholithiasis and cholelithiasis in the MRCP images, producing good performance in tests, differentiating them from "normal" MRCP images. With the high success rate of over 90%, refinement of the scheme could be applicable in the clinical environment as a tool in aiding diagnosis, with possible applications in telemedicine. (c) 2006 Elsevier Ltd. All rights reserved.
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spelling mmu-30222011-09-29T06:15:34Z http://shdl.mmu.edu.my/3022/ Stone detection in MRCP images using controlled region growing LOGESWARAN, R ESWARAN, C T Technology (General) QA75.5-76.95 Electronic computers. Computer science Stones in the biliary tract are routinely identified using MRCP (magnetic resonance cholangiopancreatography). The noisy nature of the images, as well as varying intensity, size and location of the stones, defeat most automatic detection algorithms, making computer-aided diagnosis difficult. This paper proposes a multi-stage segment-based scheme for semi-automated detection of choledocholithiasis and cholelithiasis in the MRCP images, producing good performance in tests, differentiating them from "normal" MRCP images. With the high success rate of over 90%, refinement of the scheme could be applicable in the clinical environment as a tool in aiding diagnosis, with possible applications in telemedicine. (c) 2006 Elsevier Ltd. All rights reserved. PERGAMON-ELSEVIER SCIENCE LTD 2007-08 Article NonPeerReviewed LOGESWARAN, R and ESWARAN, C (2007) Stone detection in MRCP images using controlled region growing. Computers in Biology and Medicine, 37 (8). pp. 1084-1091. ISSN 00104825 http://dx.doi.org/10.1016/j.compbiomed.2006.09.008 doi:10.1016/j.compbiomed.2006.09.008 doi:10.1016/j.compbiomed.2006.09.008
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
LOGESWARAN, R
ESWARAN, C
Stone detection in MRCP images using controlled region growing
title Stone detection in MRCP images using controlled region growing
title_full Stone detection in MRCP images using controlled region growing
title_fullStr Stone detection in MRCP images using controlled region growing
title_full_unstemmed Stone detection in MRCP images using controlled region growing
title_short Stone detection in MRCP images using controlled region growing
title_sort stone detection in mrcp images using controlled region growing
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/3022/
http://shdl.mmu.edu.my/3022/
http://shdl.mmu.edu.my/3022/